Exploring Complex Mental Health Symptoms via Classifying Social Media Data with Explainable LLMs
Journal:
arXiv
Published Date:
Dec 9, 2024
Abstract
We propose a pipeline for gaining insights into complex diseases by training
LLMs on challenging social media text data classification tasks, obtaining
explanations for the classification outputs, and performing qualitative and
quantitative analysis on the explanations. We report initial results on
predicting, explaining, and systematizing the explanations of predicted reports
on mental health concerns in people reporting Lyme disease concerns. We report
initial results on predicting future ADHD concerns for people reporting anxiety
disorder concerns, and demonstrate preliminary results on visualizing the
explanations for predicting that a person with anxiety concerns will in the
future have ADHD concerns.
